EP1987493A1 - Verfahren und system zum rekonstruieren eines modells eines objekts - Google Patents

Verfahren und system zum rekonstruieren eines modells eines objekts

Info

Publication number
EP1987493A1
EP1987493A1 EP06708931A EP06708931A EP1987493A1 EP 1987493 A1 EP1987493 A1 EP 1987493A1 EP 06708931 A EP06708931 A EP 06708931A EP 06708931 A EP06708931 A EP 06708931A EP 1987493 A1 EP1987493 A1 EP 1987493A1
Authority
EP
European Patent Office
Prior art keywords
interest
model
point
seed point
marked
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP06708931A
Other languages
English (en)
French (fr)
Other versions
EP1987493A4 (de
Inventor
Martti Kalke
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
GE Healthcare Finland Oy
Original Assignee
GE Healthcare Finland Oy
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by GE Healthcare Finland Oy filed Critical GE Healthcare Finland Oy
Publication of EP1987493A1 publication Critical patent/EP1987493A1/de
Publication of EP1987493A4 publication Critical patent/EP1987493A4/de
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G06T7/564—Depth or shape recovery from multiple images from contours
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/003—Reconstruction from projections, e.g. tomography
    • G06T11/005—Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2211/00—Image generation
    • G06T2211/40—Computed tomography
    • G06T2211/424—Iterative
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2211/00—Image generation
    • G06T2211/40—Computed tomography
    • G06T2211/436—Limited angle

Definitions

  • the invention relates to a method, system and computer program product for reconstructing of projection data of a model of an object according to the preamble of claims 1 , 7 and 8 correspondingly. Especially the invention relates to reconstructing of projection data of a model of an object gathered by X-ray imaging.
  • the attenuation of X-rays in one volume unit (voxel) inside the volume is typically defined basing on the values of the pixel values on projection images. This can be done, like in known prior art, basing on the fact that each pixel value is an integral of attenuation along the X-ray beam in the volume. Therefore an inner structure and details of an object can be determined very accurately.
  • the object of the invention is achieved by marking a point of at least one object of interest from at least two projection images as a seed point, where said point locates inside the object of interest in the corresponding projection image, and reconstructing a model of the object by adding plurality of elementary object elements around the marked seed point in each direction until a criteria, such as likelihood criteria, is fulfilled in said direction. Further the object of the invention is achieved by connecting priori information relating to the object of interest with said elementary object elements, where said priori information concerns at least one of the following character of the object of interest: size, shape, type, location, volume and density.
  • the invention relates to a method of reconstructing a model of an object in medical imaging, where the method comprises the steps of:
  • the invention further relates to a system for reconstructing a model of an object in medical imaging, where the system is adapted, after a point of at least one object of interest from at least two projection images is marked as a seed point, where said point locates inside the object of interest in the corresponding projection image, to reconstruct the model of the object of projection data by adding plurality of elementary object elements, with which priori information relating to the object of interest is connected, around the marked seed point in each direction until a criteria is fulfilled in said direction.
  • the invention relates to a computer program product for reconstructing a model of an object in medical imaging, where the computer program product, when run on a computer, is adapted, after a point of at least one object of interest from at least two projection images is marked as a seed point, where said point locates inside the object of interest in the corresponding projection image, to reconstruct the model of the object of projection data by adding plurality of elementary object elements, with which priori information relating to the object of interest is connected, around the marked seed point in each direction until a criteria is fulfilled in said direction.
  • gray scales of voxels of a projection image including also image information of objects are first determined, whereafter a gray-scale image is segmented. Then, an arbitrary point of an object or objects of interest from at least two projection images is/are marked as a seed point(s), where the point locates inside the object, a surface of which is elected to being reconstructed. Because of this marking step, the reconstruction "knows" the number of objects and also the location of one voxel per object (a seed point), which is inside the object of interest in the corresponding projection image unambiguously.
  • the reconstruction of projection data of the model is advantageously implemented by adding plurality of elementary object element around the marked seed point in each direction until a criteria is fulfilled in said direction.
  • the shape and/or size of the elementary object element added around the marked seed point may depend on characters of a tissue in question and its typical geometrical characters. Further according to an embodiment of the invention said criteria is fulfilled when value of model in a certain place in the surface model differs from corresponding imaged value over predetermined degree.
  • priori information relating to the object of interest is connected with elementary object element added around the seed point.
  • Used priori information relates to at least one of the following character of the object of interest, such as for example size, shape, type, location, volume and density.
  • priori information may relate to characters of a tissue in question and its typical geometrical characters, whereupon the shape and/or size of the elementary object element to be added around the seed point can be optimised, for example.
  • Number of objects can be marked in the image, whereupon even 3D model can be reconstructed describing relation between different tissues, such as in implatology imaging.
  • the volume can be viewed in slices or as a 3D volume normally, for example.
  • the invention offers numerous advantages over known prior art, such as a surface model of an object, which can be directly reconstructed from a segmented image according to the invention. Moreover the use of priori information with seed point method the reconstruction process is fast and accurate.
  • Figure 1 illustrates a flow diagram of an exemplary method of reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention
  • Figure 2 illustrates an exemplary system for reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention
  • Figure 3 illustrates an exemplary computer program product for reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention.
  • Figure 1 illustrates a flow diagram 100 of an exemplary method of reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention.
  • step 102 gray scales of voxels of a projection image including also image information of objects are determined, whereafter in step 104 a gray-scale image is segmented.
  • step 106 an arbitrary point of an object or objects of interest from at least two projection images is/are marked as a seed point(s), where the point locates inside the object, a surface of which is elected to being reconstructed.
  • step 108 priori information is connected with said seed point(s) and also with the object being reconstructed, whereupon the shape and/or size of the elementary object element added around the marked seed point can be optimised based on the characters of a tissue in question and its typical geometrical characters, for example. Furthermore the characters of the added elementary object elements may depend on size, shape, type, and location of the object of interest, for example.
  • step 110 the reconstruction of projection data of the surface model is advantageously implemented by adding plurality of elementary object element around the marked seed point in each direction until the likelihood criteria is fulfilled in said direction.
  • step 112 it is checked whether the likelihood criteria is fulfilled. If the likelihood criteria is fulfilled in each direction the reconstructed surface model can be displayed in step 114. Otherwise further elementary object elements are added in step 110 at least in direction, where the likelihood criteria is not fulfilled yet.
  • the likelihood criteria is advantageously fulfilled when value of model in a certain place in the surface model differs from corresponding imaged value over predetermined degree.
  • steps 102 and 104 are optional and they are not to be interpreted to pose limitations to the applicability of the appended claims.
  • Figure 2 illustrates an exemplary system 200 for reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention, where the system advantageously comprises display 202 for displaying projection images.
  • the system 200 also comprises means 204, such as a control means, for allowing to marking of a seed point of an object or objects of interest from at least two projection images.
  • system 200 comprises means 206 for detecting likelihood criteria, whether it is fulfilled, and means 208 for generating elementary object element, which shape and/or size is optimised based on the characters of a tissue in question and its typical geometrical characters, for example. Furthermore the characters of the added elementary object elements may depend on size, shape, type, location, volume and density of the object of interest, for example.
  • system 200 comprises means 210 for adding elementary object elements around the seed point and means for creating and displaying the reconstructed surface model 212 on the display 202, such as an implantology image of a tooth. Furthermore a segmented 3D model from the reconstructed surfaces of plurality of objects can be created and displayed by means 210.
  • the system can be implemented by a computer 214, but this is, however, optional.
  • Figure 3 illustrates an exemplary computer program product 300 for reconstructing of projection data of a surface model of an object in medical imaging according to an advantageous embodiment of the invention.
  • the computer program product may advantageously comprise the following code means for performing a certain task, when said computer program product 300 is run on the computer 214, such as code means 304 for connecting a given seed point with a certain object or objects of interest.
  • the computer program product 300 comprises code means 306 for detecting likelihood criteria, whether it is fulfilled, and code means 308 for generating elementary object element, which shape and/or size is optimised based on the characters of a tissue in question and its typical geometrical characters, for example. Furthermore the characters of the added elementary object elements may depend on size, shape, type, location, volume and density of the object of interest, for example.
  • the computer program product 300 comprises code means 310 for adding elementary object elements around the seed point and means for creating and displaying the reconstructed surface model 212 on the display 202, such as an implantology image of a tooth. Furthermore a segmented 3D model from the reconstructed surfaces of plurality of objects can be created and displayed by means 310.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
EP06708931A 2006-02-24 2006-02-24 Verfahren und system zum rekonstruieren eines modells eines objekts Ceased EP1987493A4 (de)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/FI2006/000072 WO2007096453A1 (en) 2006-02-24 2006-02-24 Method and system for reconstructing a model of an object

Publications (2)

Publication Number Publication Date
EP1987493A1 true EP1987493A1 (de) 2008-11-05
EP1987493A4 EP1987493A4 (de) 2012-08-08

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
EP06708931A Ceased EP1987493A4 (de) 2006-02-24 2006-02-24 Verfahren und system zum rekonstruieren eines modells eines objekts

Country Status (3)

Country Link
US (1) US8284196B2 (de)
EP (1) EP1987493A4 (de)
WO (1) WO2007096453A1 (de)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9092895B2 (en) 2010-12-20 2015-07-28 General Electric Company System and method for soft-field reconstruction
CN102208117A (zh) * 2011-05-04 2011-10-05 西安电子科技大学 脊椎的三维几何与有限元混合模型的构建方法
CN106846386B (zh) * 2017-02-08 2019-06-28 南通大学 基于roi和共形几何代数特征不变量的3d颅部图像配准方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004068412A1 (en) * 2003-01-31 2004-08-12 Philips Intellectual Property & Standards Gmbh Method for the reconstruction of three-dimensional objects

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6246784B1 (en) * 1997-08-19 2001-06-12 The United States Of America As Represented By The Department Of Health And Human Services Method for segmenting medical images and detecting surface anomalies in anatomical structures
US7072515B2 (en) * 2001-01-26 2006-07-04 Rensselaer Polytechnic Institute Method and apparatus for automatically tracing line-structure images
US6961404B2 (en) 2002-09-26 2005-11-01 Eastman Kodak Company Method and system for reconstructing an image from projection data acquired by a cone beam computed tomography system
US7787673B2 (en) * 2004-12-21 2010-08-31 Siemens Medical Solutions Usa, Inc. Method and apparatus for airway detection and segmentation using 3D morphological operators

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004068412A1 (en) * 2003-01-31 2004-08-12 Philips Intellectual Property & Standards Gmbh Method for the reconstruction of three-dimensional objects

Non-Patent Citations (3)

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Title
HASSAN ET AL: "A volumetric 3D model of the human jaw", INTERNATIONAL CONGRESS SERIES, EXCERPTA MEDICA, AMSTERDAM, NL, vol. 1281, 1 May 2005 (2005-05-01), pages 1244-1249, XP005081854, ISSN: 0531-5131, DOI: 10.1016/J.ICS.2005.03.345 *
See also references of WO2007096453A1 *
SOUSSEN C ET AL: "Contour-based models for 3D binary reconstruction in X-ray tomography", AIP CONFERENCE PROCEEDINGS, AMERICAN INSTITUTE OF PHYSICS, NEW YORK, US, no. 568, 1 January 2001 (2001-01-01), pages 543-554, XP007908746, ISSN: 0094-243X, DOI: 10.1063/1.1381916 *

Also Published As

Publication number Publication date
US20090237402A1 (en) 2009-09-24
WO2007096453A1 (en) 2007-08-30
US8284196B2 (en) 2012-10-09
EP1987493A4 (de) 2012-08-08

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